Github user jkbradley commented on a diff in the pull request:

    https://github.com/apache/spark/pull/2595#discussion_r18297121
  
    --- Diff: 
mllib/src/main/scala/org/apache/spark/mllib/tree/DecisionTree.scala ---
    @@ -518,30 +512,69 @@ object DecisionTree extends Serializable with Logging 
{
           agg
         }
     
    -    // Calculate bin aggregates.
    -    timer.start("aggregation")
    -    val binAggregates: DTStatsAggregator = {
    -      val initAgg = if (metadata.subsamplingFeatures) {
    -        new DTStatsAggregatorSubsampledFeatures(metadata, 
treeToNodeToIndexInfo)
    -      } else {
    -        new DTStatsAggregatorFixedFeatures(metadata, numNodes)
    +    /**
    +     * Get node index in group --> features indices map,
    +     * which is a short cut to find feature indices for a node given node 
index in group
    +     * @param treeToNodeToIndexInfo
    +     * @return
    +     */
    +    def getNodeToFeatures(treeToNodeToIndexInfo: Map[Int, Map[Int, 
NodeIndexInfo]])
    +      :Map[Int, Option[Array[Int]]] = {
    +      val mutableNodeToFeatures = new mutable.HashMap[Int, 
Option[Array[Int]]]()
    +      treeToNodeToIndexInfo.values.foreach { nodeIdToNodeInfo =>
    +        nodeIdToNodeInfo.values.foreach { nodeIndexInfo =>
    +          mutableNodeToFeatures(nodeIndexInfo.nodeIndexInGroup) = 
nodeIndexInfo.featureSubset
    +        }
           }
    -      input.treeAggregate(initAgg)(binSeqOp, DTStatsAggregator.binCombOp)
    +      mutableNodeToFeatures.toMap
         }
    -    timer.stop("aggregation")
     
         // Calculate best splits for all nodes in the group
         timer.start("chooseSplits")
     
    +    // In each partition, iterate all instances and compute aggregate 
stats for each node,
    +    // yield an (nodeIndex, nodeAggregateStats) pair for each node.
    +    // After a `reduceByKey` operation,
    +    // stats of a node will be shuffled to a particular partition and be 
combined together,
    +    // then best splits for nodes are found there.
    +    // Finally, only best Splits for nodes are collected to driver to 
construct decision tree.
    +    val nodeToFeatures = getNodeToFeatures(treeToNodeToIndexInfo)
    +    val nodeToFeaturesBc = input.sparkContext.broadcast(nodeToFeatures)
    +    val nodeToBestSplits =
    +      input.mapPartitions { points =>
    +        // Construct a nodeStatsAggregators array to hold node aggregate 
stats,
    +        // each node will have a nodeStatsAggregator
    +        val numNodes = nodeToFeatures.keys.size
    --- End diff --
    
    numNodes has already been computed above; reuse that value in this closure?


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